research-article

Public Access

Tango of edge and cloud execution for reliability

Authors:

Shikhar Suryavansh,

Chandan Bothra,

Saurabh BagchiAuthors Info & Claims

MECC '19: Proceedings of the 4th Workshop on Middleware for Edge Clouds & Cloudlets

Pages 10 - 15

https://doi.org/10.1145/3366614.3368103

Published: 09 December 2019 Publication History

Abstract

The increasing cost of cloud services and the need for decentralization of servers has led to a rise of interest in Edge computing. Edge computing brings the servers closer to the end users which helps in reducing network latency. However, the presence of multiple edge servers adversely affects the reliability due to difficulty in maintenance of heterogeneous servers. This paper aims at evaluating the performance of various server configuration models in edge computing using EdgeCloudSim, a popular simulator for edge computing. The performance is evaluated in terms of service time and percentage of failed tasks for an Augmented Reality application.

We evaluated the performance of the following edge computing models, Exclusive: Mobile only, Edge only, Cloud only; and Hybrid: Edge & Cloud hybrid with load-balancing on the Edge, and Mobile & Edge hybrid. We analyzed the impact of variation of different parameters such as WAN bandwidth, cost of cloud resources, heterogeneity of edge servers, etc., on the performance of the edge computing models. We show that due to variation in the above parameters, the exclusive models are not sufficient for computational requirements and there is a need for hybrid edge computing models.

References

[1]

[n.d.]. AWS IoT Greengrass. https://aws.amazon.com/greengrass/.

[2]

[n.d.]. AWS IoT Greengrass Usage. https://discovery.hgdata.com/product/aws-iot-greengrass.

[3]

[n.d.]. CloudFront. https://aws.amazon.com/cloudfront/.

[4]

[n.d.]. Lambda@Edge. https://aws.amazon.com/lambda/edge/.

[5]

Rodrigo N. Calheiros, Rajiv Ranjan, César A. F. De Rose, and Rajkumar Buyya. 2009. CloudSim: A Novel Framework for Modeling and Simulation of Cloud Computing Infrastructures and Services. CoRR abs/0903.2525 (2009).

[6]

Eduardo Cuervo, Aruna Balasubramanian, Dae-ki Cho, Alec Wolman, Stefan Saroiu, Ranveer Chandra, and Paramvir Bahl. 2010. MAUI: Making Smartphones Last Longer with Code Offload. In Proceedings of the 8th International Conference on Mobile Systems, Applications, and Services (MobiSys '10). ACM, New York, NY, USA, 49--62.

Digital Library

[7]

M. T. Diallo, F. Fieau, and J. Hennequin. 2014. Impacts of video Quality of Experience on User Engagement in a live event. In 2014 IEEE International Conference on Multimedia and Expo Workshops (ICMEW). 1--7.

[8]

Hoang T. Dinh, Chonho Lee, Dusit Niyato, and Ping Wang. 2013. A survey of mobile cloud computing: architecture, applications, and approaches. Wireless Communications and Mobile Computing 13, 18 (2013), 1587--1611. arXiv:https://onlinelibrary.wiley.com/doi/pdf/10.1002/wcm.1203

[9]

Wenlu Hu, Ying Gao, Kiryong Ha, Junjue Wang, Brandon Amos, Zhuo Chen, Padmanabhan Pillai, and Mahadev Satyanarayanan. 2016. Quantifying the Impact of Edge Computing on Mobile Applications. In Proceedings of the 7th ACM SIGOPS Asia-Pacific Workshop on Systems (APSys '16). ACM, New York, NY, USA, Article 5, 8 pages.

Digital Library

[10]

Y. Jararweh, A. Doulat, O. AlQudah, E. Ahmed, M. Al-Ayyoub, and E. Benkhelifa. 2016. The future of mobile cloud computing: Integrating cloudlets and Mobile Edge Computing. In 2016 23rd International Conference on Telecommunications (ICT). 1--5.

[11]

Michael Nelson, Beng-Hong Lim, and Greg Hutchins. 2005. Fast Transparent Migration for Virtual Machines. In Proceedings of the Annual Conference on USENIX Annual Technical Conference (ATEC '05). USENIX Association, Berkeley, CA, USA, 25--25. http://dl.acm.org/citation.cfm?id=1247360.1247385

Digital Library

[12]

M. Satyanarayanan. 2017. The Emergence of Edge Computing. Computer 50, 1 (Jan 2017), 30--39.

Digital Library

[13]

Mahadev Satyanarayanan, Paramvir Bahl, Ramón Caceres, and Nigel Davies. 2009. The Case for VM-Based Cloudlets in Mobile Computing. IEEE Pervasive Computing 8, 4 (Oct. 2009), 14--23.

Digital Library

[14]

W. Shi, J. Cao, Q. Zhang, Y. Li, and L. Xu. 2016. Edge Computing: Vision and Challenges. IEEE Internet of Things Journal 3, 5 (Oct 2016), 637--646.

[15]

C. Sonmez, A. Ozgovde, and C. Ersoy. 2017. EdgeCloudSim: An environment for performance evaluation of Edge Computing systems. In 2017 Second International Conference on Fog and Mobile Edge Computing (FMEC). 39--44.

[16]

Tim Verbelen, Pieter Simoens, Filip De Turck, and Bart Dhoedt. 2012. Cloudlets: Bringing the Cloud to the Mobile User. In Proceedings of the Third ACM Workshop on Mobile Cloud Computing and Services (MCS '12). ACM, New York, NY, USA, 29--36.

Digital Library

[17]

Paul Wood, Heng Zhang, Muhammad-Bilal Siddiqui, and Saurabh Bagchi. 2017. Dependability in Edge Computing. CoRR abs/1710.11222 (2017). arXiv:1710.11222 http://arxiv.org/abs/1710.11222

[18]

Ran Xu, Jinkyu Koo, Rakesh Kumar, Peter Bai, Subrata Mitra, Sasa Misailovic, and Saurabh Bagchi. 2018. VideoChef: Efficient Approximation for Streaming Video Processing Pipelines. In 2018 USENIX Annual Technical Conference (USENIX ATC 18). USENIX Association, Boston, MA, 43--56. https://www.usenix.org/conference/atc18/presentation/xu-ran

[19]

Y. Yu. 2016. Mobile edge computing towards 5G: Vision, recent progress, and open challenges. China Communications 13, Supplement2 (N 2016), 89--99.

Cited By

Kolosov OAktaş MSoljanin EYadgar G(2023)Theory vs. Practice in Modeling Edge Storage Systems2023 IEEE International Performance, Computing, and Communications Conference (IPCCC)10.1109/IPCCC59175.2023.10253868(313-322)Online publication date: 17-Nov-2023
https://doi.org/10.1109/IPCCC59175.2023.10253868
Pourreza MNarasimhan P(2023)A Survey of Faults and Fault-Injection Techniques in Edge Computing Systems2023 IEEE International Conference on Edge Computing and Communications (EDGE)10.1109/EDGE60047.2023.00021(63-71)Online publication date: Jul-2023
https://doi.org/10.1109/EDGE60047.2023.00021
Abilkaiyrkyzy AElhagry ALaamarti FSaddik A(2023)Metaverse Key Requirements and Platforms SurveyIEEE Access10.1109/ACCESS.2023.332584411(117765-117787)Online publication date: 2023
https://doi.org/10.1109/ACCESS.2023.3325844
Show More Cited By

Index Terms

Tango of edge and cloud execution for reliability
1. Computing methodologies
  1. Modeling and simulation
    1. Simulation evaluation
2. General and reference
  1. Cross-computing tools and techniques
    1. Performance
    2. Reliability

Recommendations

Microservice-Oriented Edge Server Deployment in Cloud-Edge System
Security, Privacy, and Anonymity in Computation, Communication, and Storage
Abstract
With the advent of the fifth generation communication system (5G), edge computing has been more widely used. In edge computing, in order to maximize the use of resources, and to deal with the computation request as soon as possible, the layout and ...
Edge computing: A survey
Abstract
In recent years, the Edge computing paradigm has gained considerable popularity in academic and industrial circles. It serves as a key enabler for many future technologies like 5G, Internet of Things (IoT), augmented reality and ...
Highlights
- A comprehensive survey on edge computing, i.e., Fog, Mobile-edge and Cloudlet.
- ...
Towards the Decentralised Cloud: Survey on Approaches and Challenges for Mobile, Ad hoc, and Edge Computing

Cloud computing emerged as a centralised paradigm that made “infinite” computing resources available on demand. Nevertheless, the ever-increasing computing capacities present on smart connected things and devices calls for the decentralisation of Cloud ...

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences

MECC '19: Proceedings of the 4th Workshop on Middleware for Edge Clouds & Cloudlets

December 2019

21 pages

ISBN:9781450370325

DOI:10.1145/3366614

General Chairs:
Rolando Martins
University of Porto, Portugal
,
Herve Paulino
University Nova of Lisbon, Portugal
,
Luis Veiga
Technical University of Lisbon, Portugal

Copyright © 2019 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Sponsors

ACM: Association for Computing Machinery

In-Cooperation

USENIX Assoc: USENIX Assoc
IFIP

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 09 December 2019

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article

Funding Sources

Northrop Grumman Corporation
National Science Foundation

Conference

Middleware '19

Sponsor:

ACM

Middleware '19: 20th International Middleware Conference

December 9 - 13, 2019

California, Davis

Acceptance Rates

Overall Acceptance Rate 4 of 9 submissions, 44%

Upcoming Conference

MIDDLEWARE '24

25th International Middleware Conference

December 2 - 6, 2024

Hong Kong , Hong Kong

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

12
Total Citations
View Citations
472
Total Downloads

Downloads (Last 12 months)102
Downloads (Last 6 weeks)12

Reflects downloads up to 15 Sep 2024

Other Metrics

View Author Metrics

Citations

Cited By

Kolosov OAktaş MSoljanin EYadgar G(2023)Theory vs. Practice in Modeling Edge Storage Systems2023 IEEE International Performance, Computing, and Communications Conference (IPCCC)10.1109/IPCCC59175.2023.10253868(313-322)Online publication date: 17-Nov-2023
https://doi.org/10.1109/IPCCC59175.2023.10253868
Pourreza MNarasimhan P(2023)A Survey of Faults and Fault-Injection Techniques in Edge Computing Systems2023 IEEE International Conference on Edge Computing and Communications (EDGE)10.1109/EDGE60047.2023.00021(63-71)Online publication date: Jul-2023
https://doi.org/10.1109/EDGE60047.2023.00021
Abilkaiyrkyzy AElhagry ALaamarti FSaddik A(2023)Metaverse Key Requirements and Platforms SurveyIEEE Access10.1109/ACCESS.2023.332584411(117765-117787)Online publication date: 2023
https://doi.org/10.1109/ACCESS.2023.3325844
Li BHe QCui GXia XChen FJin HYang Y(2022)READ: Robustness-Oriented Edge Application Deployment in Edge Computing EnvironmentIEEE Transactions on Services Computing10.1109/TSC.2020.301531615:3(1746-1759)Online publication date: 1-May-2022
https://doi.org/10.1109/TSC.2020.3015316
Runji JLee YChu C(2022)Systematic Literature Review on Augmented Reality-Based Maintenance Applications in Manufacturing Centered on Operator NeedsInternational Journal of Precision Engineering and Manufacturing-Green Technology10.1007/s40684-022-00444-w10:2(567-585)Online publication date: 7-Jun-2022
https://doi.org/10.1007/s40684-022-00444-w
Savaglio CFortino G(2021)A Simulation-driven Methodology for IoT Data Mining Based on Edge ComputingACM Transactions on Internet Technology10.1145/340244421:2(1-22)Online publication date: 3-Mar-2021
https://dl.acm.org/doi/10.1145/3402444
Aloi GFortino GGravina RPace PSavaglio C(2021)Simulation-Driven Platform for Edge-Based AAL SystemsIEEE Journal on Selected Areas in Communications10.1109/JSAC.2020.302154439:2(446-462)Online publication date: Feb-2021
https://doi.org/10.1109/JSAC.2020.3021544
Theera-Ampornpunt NSuryavansh SManchanda SPanta RJoshi KAmmar MChiang MBagchi SValois FJulien CMurphy AGnawali O(2020)AppStreamer: Reducing Storage Requirements of Mobile Games through Predictive StreamingProceedings of the 2020 International Conference on Embedded Wireless Systems and Networks10.5555/3400306.3400312(37-48)Online publication date: 17-Feb-2020
https://dl.acm.org/doi/10.5555/3400306.3400312
Akbar ALewis PWanner E(2020)A Self-Aware and Scalable Solution for Efficient Mobile-Cloud Hybrid RoboticsFrontiers in Robotics and AI10.3389/frobt.2020.001027Online publication date: 5-Aug-2020
https://doi.org/10.3389/frobt.2020.00102
Silva JMarques ELopes LSilva F(2020)Jay: Adaptive Computation Offloading for Hybrid Cloud Environments2020 Fifth International Conference on Fog and Mobile Edge Computing (FMEC)10.1109/FMEC49853.2020.9144950(54-61)Online publication date: Apr-2020
https://doi.org/10.1109/FMEC49853.2020.9144950
Show More Cited By

View Options

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Get Access

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

Media

Figures

Other

Tables

View Table of Contents